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Ang Davies, Andy Brass, Alan Davies, Iliada Eleftheriou, Patrick Mitchell, and Fran Hooley

Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is designed for health and social care professionals in the UK. It is relevant to any non-UK healthcare professionals who want to understand the basic concepts, challenges and opportunities of AI in their respective healthcare systems. The course is also useful for those with relevant skills outside the NHS who have an interest in new professional groups emerging from AI, such as clinical data scientists, medical software engineers, and digital medicine specialists. You can use the hashtag #FLTransformAIHealthcare to talk about this course on social media.

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Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is designed for health and social care professionals in the UK. It is relevant to any non-UK healthcare professionals who want to understand the basic concepts, challenges and opportunities of AI in their respective healthcare systems. The course is also useful for those with relevant skills outside the NHS who have an interest in new professional groups emerging from AI, such as clinical data scientists, medical software engineers, and digital medicine specialists. You can use the hashtag #FLTransformAIHealthcare to talk about this course on social media.

Topics Covered

  • Introduction to the wider context of the challenges and opportunities impacting on Healthcare as outlined in the Topol Report
  • New and upcoming technological developments and their ethical, social, and legal implications
  • Wider patient pathway focusing on specific cases and datasets from different areas such as Nursing, Radiography and Deep Learning /Cancer
  • Challenges of governance, ‘team science’ and interdisciplinary working, data quality in the NHS
  • Practice-based case studies illustrating where the skills gaps have been addressed
  • Practical and practice-based CPD activities

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Reviews summary

Foundational ai for healthcare professionals

Learners say this course provides a comprehensive overview and a strong foundation for understanding AI's role in healthcare. It is particularly praised for its focus on ethical, social, and legal implications, and its use of practical case studies that make complex concepts accessible. Many found it highly relevant to their professional roles as healthcare professionals, administrators, or managers. However, some students note that the course is high-level and may lack technical depth, making it less suitable for those with an advanced AI background or seeking hands-on application. It is described as excellent for demystifying AI for non-technical individuals and those looking for a broad understanding of digital transformation in healthcare.
Best suited for those seeking a foundational understanding, especially non-technical professionals.
"Excellent course! It demystified AI for me as a nurse. The content was easy to understand, even for someone without a tech background."
"I enjoyed this course. It gave me a much-needed perspective on AI's role in transforming healthcare."
"It might be good for administrators, but not for technical roles."
Emphasizes crucial ethical aspects and real-world case studies.
"The modules on ethical implications and data governance were particularly strong and highly relevant to my role..."
"The ethical considerations were well-explained. The real-world case studies were incredibly helpful..."
"It highlights the challenges and opportunities effectively. I particularly liked the module on data quality in the NHS."
Provides a broad, accessible introduction to AI in healthcare.
"This course was truly insightful, providing a comprehensive overview of AI's potential in healthcare."
"This course provided a fantastic introduction to AI in healthcare. It's well-structured, easy to follow..."
"It's a fantastic foundation for understanding the landscape of AI in healthcare..."
Some content may feel repetitive or could benefit from newer examples.
"My only minor critique is that some content felt slightly repetitive across modules..."
"...could benefit from more recent examples or updated statistics. The discussions were sometimes superficial."
Provides a broad overview but lacks technical or advanced depth.
"Good course, though sometimes a bit high-level for someone looking for deep technical details."
"The course is okay. It covers a lot of ground but feels more like an introduction than an in-depth study."
"Disappointed with the depth. As an AI researcher, I found the course too superficial."

Activities

Coming soon We're preparing activities for AI for Healthcare: Equipping the Workforce for Digital Transformation. These are activities you can do either before, during, or after a course.

Career center

Learners who complete AI for Healthcare: Equipping the Workforce for Digital Transformation will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.
A textbook that presents AI from a computational perspective, covering topics such as agents, knowledge representation, reasoning, and planning. Suitable for readers with a background in computer science or mathematics.
A classic textbook on reinforcement learning, a subfield of AI concerned with learning from interaction with the environment. Covers both theoretical concepts and practical algorithms, with a focus on real-world applications.
A comprehensive textbook that provides a broad overview of the field, covering topics such as problem-solving, learning, machine learning, and natural language processing. Suitable for both beginners and advanced learners.
A highly cited and influential book that focuses on deep learning, a subfield of AI concerned with constructing models for complex data. Covers theoretical concepts, popular algorithms, and practical applications.
A practical guide to natural language processing (NLP) using Python, covering topics such as text classification, sentiment analysis, and machine translation. Suitable for beginners with some programming experience.
A short but powerful book that explores the potential benefits and risks of AI, as well as the ethical dilemmas that need to be addressed as AI becomes more advanced.
A comprehensive German-language textbook that provides a broad overview of AI, covering topics such as search, knowledge representation, and machine learning. Suitable for both beginners and advanced learners.
A French-language textbook that focuses on machine learning, a subfield of AI. Covers topics such as supervised learning, unsupervised learning, and deep learning. Suitable for beginners with some programming experience.
A comprehensive textbook that covers probabilistic graphical models (PGMs), a powerful tool for representing and reasoning about complex systems. Suitable for advanced learners with a background in probability and statistics.
Provides a comprehensive overview of the field of global health, which is concerned with the health of populations around the world. It is an excellent resource for anyone interested in learning more about the global health approach to healthcare.
Provides a comprehensive overview of the management of healthcare organizations. It is an excellent resource for anyone interested in learning more about the business of healthcare.
Provides a comprehensive overview of the field of medical sociology, which examines the social causes and consequences of illness and health care. It is an excellent resource for anyone interested in learning more about the social side of healthcare.
Provides a comprehensive overview of epidemiology, the study of the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. It is an excellent resource for anyone interested in learning more about public health.
Provides a comprehensive overview of the healthcare financial management system, including budgeting, cost accounting, and reimbursement mechanisms. It is an excellent resource for anyone interested in learning more about the business side of healthcare.

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